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Category: deep learning

2nd place in ICDAR 2019 Robust Reading Challenge on Reading Chinese Text on Signboard

2nd place in ICDAR 2019 Robust Reading Challenge on Reading Chinese Text on Signboard, only slightly worse than Tencent (0.8150 vs. 0.8144) 2019年, 在美团主办的图像中的中文店铺名识别竞赛第二, 惜败于腾讯 (0.8150 vs. 0.8144) https://rrc.cvc.uab.es/files/ICDAR2019-ReCTS.pdf

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3rd Place in the AI edge contest (image segmentation)

https://lp.signate.jp/ai-edge-contest/en/ We (Yifan Liu, Tong He, and Chunhua Shen) attended the AI edge contest organised by The Ministry of Economy, Trade and Industry Japan, and won the 3rd Place. The task is to create an algorithm to segment the image region corresponding to an object of interest at the pixel level. Images are captured by […]

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#1 for the MICCAI 2018 competition of Nuclei images segmentation

Zifeng Wu, Chunhua Shen, Anton van den Hegnel attended the competition of Nuclei images segmentation task and won the first place! Leaderboard (showing submitter’s ID): http://miccai.cloudapp.net/competitions/83#results   Overview Grading and diagnosis of tumors in cancer patients have traditionally been done by examination of tissue specimens under a powerful microscope by expert pathologists. While this process […]

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Our ResNet38 models are included in Wolfram Neural Net Repo

Our ResNet38 models are included in Wolfram Neural Net Repo: https://resources.wolframcloud.com/NeuralNetRepository/resources/Ademxapp-Model-A-Trained-on-ImageNet-Competition-Data https://resources.wolframcloud.com/NeuralNetRepository/resources/Ademxapp-Model-A1-Trained-on-ADE20K-Data https://resources.wolframcloud.com/NeuralNetRepository/resources/Ademxapp-Model-A1-Trained-on-Cityscapes-Data https://resources.wolframcloud.com/NeuralNetRepository/resources/Ademxapp-Model-A1-Trained-on-PASCAL-VOC2012-and-MS-COCO-Data      

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#1 on Retinal Fundus Glaucoma Challenge Segmentation task (MICCAI 2018)

  The AIML (Australian Institute for Machine Learning) team, who are Zifeng Wu, Chunhua Shen, Anton van den Hegnel, attended this medical imaging competition and won the 1st place for the task of segmentation. Leaderboard:

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Landmark detection using Generative Adversarial networks

Adversarial PoseNet: A Structure-aware Convolutional Network for Human Pose Estimation Proc. Int. Conf. Computer Vision 2017

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Recent talk at VALSE 2018 on Visual Question Answering

Slides can be accessed at https://cloudstor.aarnet.edu.au/plus/s/Oyqtc4DABsFvddb

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Monocular relative depth perception with web stereo data supervision

This work will be presented at IEEE Conf. Computer Vision and Pattern Recognition (CVPR) 2018.

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Repulsion loss: detecting pedestrians in a crowd

Detecting individual pedestrians in a crowd remains a challenging problem since the pedestrians often gather together and occlude each other in real-world scenarios. In this paper, we first explore how a state-of-the-art pedestrian detector is harmed by crowd occlusion via experimentation, providing insights into the crowd occlusion problem. Then, we propose a novel bounding box […]

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Counting maize tassels using Machine Learning

Accurately counting maize tassels is important for monitoring the growth status of maize plants. This tedious task, however, is still mainly done by manual efforts. In the context of modern plant phenotyping, automating this task is required to meet the need of large-scale analysis of genotype and phenotype. In recent years, computer vision technologies have […]

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